Wen-Kai Kevin Hsu ( ) 2014.10.29 Department of Shipping &
Transportation Management, National Kaohsiung Marine
University
Slide 2
Outline Introduction Literature Review Research method
Discussions Conclusions
Slide 3
Introduction
Slide 4
Whats the problem Global logistics and Door to Door services
lead to third party logistics or Distribution Centers getting
increasingly important. An IDC links import and export firms.
Relevant literature indicates that quality customer service and its
performance has been shown to have a direct link with import
firms/export firms performance [3]
Slide 5
Most of relevant studies focus on users service requirements
[4-5]. Few articles examine the service operations of IDCs. Service
requirements indicate what the needs of users are. service
operations indicate how to satisfy the users needs.
Slide 6
The research purpose The purpose of this paper is to examine
the service quality of IDCs. The service requirement attributes
(SRAs) of the IDCs are first investigated from the perspectives of
IDC users. A Quality Function Deployment (QFD) with fuzzy AHP model
is then proposed to translate the SRAs into the service operations
attributes (SOAs) of IDCs. Finally, as an empirical study, the IDCs
in Taiwan were investigated to validate the research model.
Slide 7
Literature Review
Slide 8
The measurement of service quality SERVQUAL Scale: Tangibles,
Reliability, Responsiveness, Assurance and Empathy. For business
customers, the SERVQUAL scale have to be revised by considering the
business features, such as port services [12-13], air cargo
services [14], shipping liner services [15], container terminal
services [16], etc
Slide 9
The service quality of IDCs Lu [18] assessed the market
segmentation of IDCs, based on shipper service requirements. 30
SRAs were created, from which 7 dimensions : value-added services,
support services, distribution services, information and
transportation services, cargo related services, consolidation
services and storage services.
Slide 10
Lu [4] examined the difference between shippers and forwarders
perspectives on those SRAs. The results indicated that four
dimensions of SRAs are found to significantly differ between
shippers and forwarders: value-added services, consolidation
services, support services and distribution services.
Slide 11
Tsai [5] discussed the determinants of shippers that use
multiple country consolidation services in IDCs. In the study, 18
SRAs were constructed, from which 5 dimensions were extracted:
Logistics information technology service, Political incentive,
Logistics operation, Logistics cost and Warehousing and
distribution.
Slide 12
Thai [19] investigated the quality of logistic services. In the
article, five factors with 20 logistics service quality (SRAs) were
validated, which named as: Customer focus quality, Order
fulfillment quality, Corporate image, Timeliness and Information
quality.
Slide 13
Hsu and Huang [20] evaluated the service requirements of
international distribution centers at ports. In the study, five
constructs with 15 SRAs were created. The results indicate IDC
users pay more attentions on Correctness of bill of lading,
Adequacy of storage space, Punctual delivery, Handlings of damaged
cargos, and Perfect delivery of cargos.
Slide 14
Quality function deployment (QFD)
Slide 15
Research Method
Slide 16
Research framework
Slide 17
The hierarchical structure of SRAs Layer 1CodeLayer 2: Service
attribute Tangibles (TG) TG1Adequacy of service branches.
TG2Adequacy of frequency and routes of transportation. TG3Adequacy
of storage space for cargo. TG3Adequate diversity of logistics
processing services. Reliability (RB) RB1Punctual delivery of cargo
RB2Correctness of shipping orders. RB3Perfect delivery of cargo.
RB4Capability to compensate for damage cargo. Responsiveness (RP)
RP1Capability to deal with emergency orders. RP2Prompt handlings of
customers complaints and appeals. RP3Promptly dealing with the
problems of damaged cargo. Empathy (EP) EP1Proactively providing
services for special cargos. EP2 Proactively providing extra
shipping information, such as new rules of customs, shipping
schedules, etc. EP3Proactively providing information about
beneficial transportation modes. Convenience (CV) CV1Provide
convenient ordering procedures. CV2Provide an information system
for cargo tracking. CV3Provide a one-stop service window.
CV4Provide diversity in electronic commerce services.
Slide 18
Questionnaire design Fot Fuzzy AHP method, a pair-wise
comparison questionnaire [27] with a nine point rating scale was
used to measure the relative perceived importance of SRAs for
respondents. Based on the hierarchical structure of the SRAs in
Table 1, an AHP questionnaire with 5 criteria with 18 sub-criteria
was created. In order to validate the scale, four IDC users were
invited to pretest the questionnaire and to check whether the
statements were clear.
Slide 19
Research sample As an empirical study, the IDCs in Taiwan were
investigated From the Directorate General of Taiwanese Customs
(2012), there are a total of 16 IDCs in Taiwan,Directorate General
of Taiwanese Customs In this paper, 4 IDCs were firstly sampled by
the proportion of the total 16 IDCs in different regions. Each
sampled IDCs was asked to provide 8 main customers currently. The
sample contains 32 subjects. The consistency index (C.I.) was
firstly used to confirm the consistency of each pair-wise
comparison matrix.
Slide 20
FeaturesRangeFrequency. Percentage (%) Type of business
Electronic and Electrical products1237.50 Plastic & Chemical
products825.00 Mechanical products618.75 Precision, Metal and
forwarder618.75 Company Age (Years) Under 10825.00 10-20412.50
21-30412.50 31-401237.50 Above 40412.50 Company Scale (Millions)
Under 101237.50 11-20618.75 21-50825.00 51-100412.50 Above 10026.25
Work experience (years) 5- 10618.75 11-15825.00 16-2026.25 Above
201650.00 Job title Assistant to president or above412.50
Manager/assistant manger1443.75 Section chief825.00 Senior
staff618.75 The respondents profile of IDC users
Slide 21
The weights of SRAs by Fuzzy AHP Layer 1: SRAs A: The global
weights of Layer 1 (%) Layer 2: SRAs B: The local weights of Layer
2(%) The global weights of Layer 2 (%) TG23.62 TG122.375.28
TG230.047.10 TG333.227.85 TG414.383.40 RB24.31 RB133.958.25
RB236.288.82 RB321.275.17 RB408.502.07 RP19.59 RP121.334.18
RP211.552.26 RP367.1213.15 EP15.83 EP135.695.65 EP233.405.29
EP330.904.89 CV16.65 CV133.015.50 CV220.773.46 CV318.563.09
CV427.664.61
Slide 22
The QFD Model The development of service operations attributes
(SOAs) is based on the organizational structure and IDCs SOPs. In
this paper, the direct divisions and their operational procedures
are employed to develop the SOAs of IDCs.
Slide 23
The operational procedures of IDCs
Slide 24
The Relationship Matrix and Correlation Matrix For the
Relational Matrix, four grades of relationship strength were
defined and rated as: strong = 5, medium =3, weak = 1, and none =
0. [23] For the Correlation Matrix, the coefficients are generally
measured in a range of [-1.0, 1.0]. Five experienced experts from
the sampled IDCs in the empirical study were invited to determine
the coefficients of the two matrixes.
Slide 25
Profiles of experts consulted in developing the Relationships
Matrix ExpertsJob titleSeniority (years)Experiences of divisions
AManage 10 SA, TR BVice Manager 24 CS, WL, TR CVice Manager 24 CA,
SA, TR EManager 26 WL, TR FManager 26 TR, WL
Results For the first layer, the IDC users pay more attention
to RB (Reliability, 24.31%) and TG (Tangible, 23.62%) constructs.
For the SRAs in the second layer, the top five SRAs IDC users
perceive importance are: RP3 (Promptly dealing with the problems of
damaged cargo, 13.15%), RB2 (Correctness of shipping orders,
8.82%), RB1 (Punctual delivery of cargo, 8.25%), TG3 (Adequacy of
storage space for cargos, 7.85%) and TG2 (Adequacy of frequency and
routes of transportation, 7.10%). For the SOAs, the five SOAs with
higher weights are: Consolidation & deconsolidation (6.751%),
Cargo stowage & discharge (6.656), Delivery scheduling
(6.573%), Value-added services (6.471%) and Business Inquiry
(6.337%). In addition, by divisions, the Warehouse Logistics
(6.390%) is the department with highest weights in SOAs.
Slide 30
Suggestions Raising the turnover rate of the storage space For
improving the SOAs: Cargo stowage & discharge, Consolidation
& deconsolidation and Logistic processing, a greater storage
space may be necessary. The relevant studies indicate that storage
service is one of the basic logistic service requirements for IDCs
[18], and adequate storage space is one of the most important SRAs
for IDCs at ports [20]. To expand the storage space may not be
feasible in short term. This paper suggests the IDC operators may
raise the turnover rate of the storage space to increase its
utilization. For example, for import cargos, IDC operators may
increase the rental rate (the rental fee increases with the storage
time of the cargos) to urge owners to reclaim their cargos as soon
as possible.
Slide 31
Enhancing the professional capability of staffs With regard to
the SOA: Delivery scheduling and Business Inquiry, the staffs
professional capability may need to be enhanced. An adequate
scheduling plan for vehicles and routes may increase the
transportation frequency and the number of routes of IDCs. This may
depend on the scheduling staffs capabilities and experiences.
Further, for any of business inquiries from customers, generally,
the staffs may also need enough professional capability to deal
with the inquiries. This paper suggests that regular training
programs for staffs could be necessary to improve their
professional capabilities.
Slide 32
Constructing an adequate Information System (IS) An IS always
plays an aid role for staffs to perform SOAs. For example, an IS
may assist the customer-service staffs to reply the inquiries of
customers correctively and punctually. An IS may propose an initial
suggestion of truck scheduling, by which, delivery staffs may
schedule the vehicles efficiently. An IS may indicate the
information of storage spaces in real time, by which warehouse
staffs may utilize the storage spaces. Thus, the post-interviews
suggested that it is important to select an adequate IS for IDC
operations. The relevant studies also indicated that information
technology significantly influence the performance [5] and quality
[20] of logistic services.
Slide 33
Conclusions
Slide 34
Academic contribution In this paper, a QFD with fuzzy AHP model
is proposed to examine the service operations of international
distribution centers (IDCs). In the relevant literature, most
studies focus on users service requirements. Few articles further
examine the service operations of IDCs. The results of this paper
not only indicate the What information (what is users needs), but
also provide How information (how to satisfy users needs).
Specifically, the How information may provide substantial
instructions for IDCs to improve their service quality
efficiently.
Slide 35
Practice contributions To validate the research model, the IDCs
in Taiwan were empirically investigated. The results indicate that
the top five SOAs with higher weights for IDCs are: Consolidation
& deconsolidation, Cargo stowage & discharge, Delivery
scheduling, Value- added services and Business inquiry. With
respect to those SOAs, some improvement policies are proposed, such
as raising the turnover rate of the storage space, enhancing the
staffs professional capabilities and constructing an adequate
Information System. The results also indicate that Warehouse
Logistics is the most important division in IDC organization. Thus,
IDC manager should pay more attention to this department.
Slide 36
Limitations and Further research The empirical study was
conducted in Taiwanese IDCs. Thus the finding may not be entirely
applicable for other areas. In practice, in order to increase
operational flexibility, IDC operators may outsource some service
operations to their partner firms. This paper did not examine the
service quality of those partner firms in detail. In practice, the
performance of partner firms may also be a determinant of service
quality for IDC operators. Thus, this may also be a topic for
further research. For better confirming the results, more
representative samples may be still necessary in future
research.
Slide 37
Reference
Slide 38
1. Ashenbaum, B., Maltz, A. and Rabinovich, E., 2005, Studies
of trends in third-party logistics usage: What can we conclude.
Transportation Journal, 147(3), 39-50. 2. Lai, K. H., 2004, Service
capability and performance of logistics service provider.
Transportation Research - Part E, l40(5), 385-399. 3. Sharma, D.,
Scholar, R., and Sahay, B. S., 2004, Modeling distributor
performance index using the system dynamics approach. Asia Pacific
Journal of Marketing and Logistics, 16(3), 37-67. 4. Lu, C. S.,
2004, An evaluation of logistics services requirements of
international distribution centers in Taiwan. Transportation
Journal, 34(4), 53-66. 5. Cheng, Y. H. and Tsai, Y. L., 2009,
Factors influencing shippers to use multiple country consolidation
services in international distribution centers. International
Journal of Production Economics, 122(11), 78-88. 6. Parasuraman,
A., Zeithaml, V. A. and Berry, L. L., 1988, SERVQUAL: A
multiple-item scale for measuring customer perceptions of service
quality. Journal of Retailing, 61(1), 12-40. 7. Peiro, J. M.,
Vicente, M. T. and Ramos, J., 2005, Employees' overestimation of
functional and relational service quality: A gap Analysis. The
Service Industries Journal, 25(6), 773-788. 8. Davis, B. R. and
Mentzer, J. T., 2006, Logistics service driven loyalty: An
exploratory study, Journal of Business Logistics, 27(2), 53-75. 9.
Seth, N., Deshmukh, S. G. and Vrat, P., 2006, A conceptual model
for quality of service in the supply chain. International Journal
of Physical Distribution & Logistics Management: 3PL, 4PL and
reverse logistics - Part 1, 36(7), 547-575. 10. Ruttle, F., 1996,
SERVQUAL: Review, critique, research agenda. European Journal of
Marketing, 30(1), 8-32.
Slide 39
11. Durvasula, S., Lysonski, S. and Mehta, S. C., 1999, Testing
the SERVQUAL scale in the business-to- business sector: The case of
ocean freight shipping service. Journal of Services Marketing,
13(2), 132-150. 12. Ugboma, C., Ogwude, I. C., Ugboma, O. and
Nnadi, K., 2007, Service quality and satisfaction measurements in
Nigerian ports: an exploration. Marine Policy and Management,
34(4), 331-346. UgbomaOgwude UgbomaNnadi 13. Pantouvakis, A.,
Chlomoudis, C. and Dimas, A., 2008, Testing the SERVQUAL scale in
the passenger port industry: a confirmatory study. Marine policy
and management, 35(5), 449-467. Pantouvakis ChlomoudisDimasTesting
the SERVQUAL scale in the passenger port industry: a confirmatory
study 14. Wang, R. T., 2007, Improving service quality using
quality function deployment-The air cargo sector of China airlines.
Journal of Air Transport Management, 13(4), 21-228. 15. Lai, C. S.,
Chen, K. K., Wang, R. L. and Lin T. S., 2009, On the service
quality gap within business customer-In case of Taiwan. Maritime
Quarterly, 18(1), 61-100. 16. Hsu, W. K. 2013, Improving the
service operations of container terminals, International Journal of
Logistics Management, 24(1), 101-116. 17. International Maritime
Organization, 1991, Port logistics: Compendium for model course,
5.02. Author, London. 18. Lu, C. S., 2003, Market segment
evaluation and international distribution centers, Transportation
Research Part E, 39(5), 49-60. 19. Thai, V. V., 2013, Logistics
service quality: conceptual model and empirical evidence.
International Journal of Logistics: Research and Applications,
16(2), 1-18. 20. Hsu, W. K and Huang, S. H., 2014, Evaluating the
service requirements of Taiwanese international port distribution
centers using IPA model based on fuzzy AHP. International Journal
of Shipping and Transport Logistics. (Forthcoming)
Slide 40
21. Hwarng, H. B. and Teo, C., 2001, Translating customers
voices into operations requirements: A QFD application in higher
education. International Journal of Quality and Reliability
Management, 18(2), 195-225. 22. Hauser, J. R. and Clausing, D.,
1988, The house of quality. Harvard Business Review, 66(3), 66-73.
23. Bottani, E. and Rizzi A., 2006, Strategic management of
logistics service: A fuzzy QFD approach. International Journal of
Production Economics, 103(2), 585-599. 24. Liang, G. S., Chou, T.
Y. and Kan, S. F., 2006, Applying fuzzy Quality Function
Development to identify service management requirements for an
ocean freight forwarders. The Quality Management, 17(5), 539-554.
25. Carnevalli, J. A. and Miguel, P. C., 2008, Review, analysis and
classification of the literature on QFD: Types of research,
difficulties and benefits. International Journal of Production
Economics, 114(2), 737-754. 26. San, M., 2003, Function Deployment
(IQFD) for discrete assembly environment. Computers and Industrial
Engineering, 45(1), 269-283. 27. Saaty, T. L., 1980, The analytic
hierarchy process. McGraw-Hill Companies Inc., New York. 28.
Buckley, J. J., 1985, Fuzzy hierarchical analysis. Fuzzy Sets and
Systems, 17(3), 233-247. 29. Hsu, W. K., 2012, Ports service
attributes for ship navigation safety. Safety Science, 50(2),
244-252. 30. Tang, J., Fung, R. Y. K., Baodong, X. and Wang, D.,
2002, A new approach to quality function deployment planning with
financial consideration. Computers and Operations Research, 29(2),
1447-1463.
Slide 41
31. Bevilacqua, M., Ciarapica, F. E. and Giacchetta, G., 2006,
A fuzzy-QFD approach to supplier selection. Journal of Purchasing
& Supply Management, 12(1), 14-27. 32. Kaufinami, A. and Gupta,
M. M., 1991, Introduction to fuzzy arithmetic: Theory and
applications, Van Nostrand Reinhold, New York. 33. Aguarn, J. and
Moreno-Jimnez, J. M., 2003, The geometric consistency index.
approximated thresholds. European Journal of Operational Research,
147(1), 137-145. 34. Yager, R. R.,1981, A procedure for ordering
fuzzy subsets of the unit interval. Information Sciences, 24(2),
143-161.